Identification of Possible Causative Agents in a Polymedicated Patient Presenting With Toxic Epidermal Necrolysis
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Bibliographic record
Abstract
PURPOSE: To present the pharmacological evaluation process in a case of a polymedicated patient presenting with toxic epidermal necrolysis (TEN). SUMMARY: A 75-year-old Caucasian polymedicated woman had been treated for hip pain with nonsteroidal anti-inflammatory drugs and pregabalin in the months preceding the apparition of an expanding papulo-erythematous rash. She had also started using new medicated eye drops for glaucoma. She presented to the emergency department of a regional hospital where all of her medications were stopped. The patient was transferred and admitted to a tertiary-care teaching hospital's specialized burn unit for significant cutaneous detachment. It was estimated that 70% to 80% of the body surface area was affected. Skin biopsy showed keratinocyte necrosis with a partial detachment of the epidermis leading to a diagnosis of TEN. The reaction ceased to progress 2 days after the discontinuation of her medications. A complete reepithelialization was objectified after 10 days. A series of steps were followed by the hospital pharmacist to determine which drugs were the most probable culprits. A complete pharmacological history was obtained and a timeline for medication use in the 3 months preceding rash apparition was established. A review of the literature was done to determine the drugs' relationships to Steven-Johnson syndrome or TEN. Using the algorithm of drug causality for epidermal necrolysis (ALDEN) score, it was determined that naproxen, pregabalin, and brinzolamide-timolol drops were all possible culprits. CONCLUSION: A systematic method for pharmacological evaluation of a polymedicated patient with TEN is presented. Naproxen, pregabalin, and brinzolamide-timolol drops were all retained as possible culprits.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it